From spreadsheets to AI
Spreadsheets have dominated all kinds of schedules within organizations for years. With all the associated risks. Yet there are now plenty of opportunities to leave the spreadsheet behind and make the step to AI. But how do you bridge the gap between your current supply chain solutions and truly AI-oriented work.
Because despite all the beautiful vistas, Gartner has shown in one of its latest reports that at least 80% of organizations continue to rely on spreadsheets for the time being. The reason for this is that for many organizations AI is still a magic word. Even if AI were mature enough for large-scale supply chain implementation, thousands of smaller companies would not have the capital to invest in these solutions.
Beyond the hype
But affordability is not the only barrier. You can’t make good use of advanced solutions until you solve more fundamental problems with the way your organization processes data.
The hype surrounding AI has had the unfortunate effect of prioritizing more pressing issues that can be addressed with simple, affordable software solutions.
Supply chain departments are increasingly taking on challenging IT projects, such as omni-channel initiatives. However, due to the changing circumstances, many IT departments are no longer able to respond to tomorrow’s challenges. This is caused by too formal a way of working in many IT departments, as a result of which she is unable to keep pace with the dynamics of the market, for which she is increasingly responsible.
Data reliability
First, addressing your organization’s immediate data reliability and digital access is the best way to solve today’s challenges. With the use of spreadsheets you run a great risk here.
If you have not already done so, addressing issues caused by low-reliability data and cross-departmental data silos should be your first priority. Solid supply chain operations are based on high-quality, reliable data that flows freely between departments. Normalizing data and bridging silos between departments are not sexy problems to solve, but if you leave it behind you will be left hopeless and unable to make the step forward.
Data science
It is therefore not surprising that data scientists and specialists spend no less than 80% of their time preparing data. Where you can expect that they focus on designing and building models.
The fact is that models are only as good as the data and formats used. It costs a lot of money to absorb all deviations and exceptions within the models. That takes a lot of coding time. So for that reason it becomes understandable that people are mainly concerned with “manipulating” the data.
To successfully meet the challenges of your supply chain, you need an organization that has a transparent structure and clear shared objectives. Too often organizations lose themselves in a flight forward under pressure from cost savings, which ultimately disappoint or even endanger the organization.
You can avoid these pitfalls by starting with a clear business plan and objectives. What results do you expect, who and what should generate which revenues and who has which responsibilities. Take the time to inform yourself about the possible AI solutions that would be applicable for your organization. But one thing is certain. The spreadsheet has had its longest time as the basis for your business decisions.
